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Beyond Synthetic Aperture Focusing: Deconvolution-Based Elevation Resolution Enhancement Using Simulated Point Spread Function for Linear Array-Based Three-dimensional Photoacoustic Imaging

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posted on 2023-12-29, 09:24 authored by Yichuan Tang, Wojciech Lesniak, Shang Gao, Yixuan Wu, Haichong Zhang, Martin Pomper
This paper introduces a deconvolution-based method to enhance the elevation resolution of a linear array-based three-dimensional (3D) photoacoustic (PA) imaging system. PA imaging combines the high contrast of optical imaging and the high spatial resolution in multi-centimeter imaging depth of ultrasound (US) imaging, providing both structural and functional information of biological tissues. Linear array-based 3D PA imaging is easily accessible and applicable for ex vivo, small animal, and human subjects. However, the elevation resolution is limited due to the single elevation focus set by the acoustic lens geometry. Previous work used synthetic aperture focusing (SAF) to enhance elevation resolution, but the achievable resolution is constrained by the effective aperture size, which is significantly narrower than that in the lateral axis. Here, we propose using Richardson-Lucy deconvolution, based on simulated point-spread-functions, to enhance elevation resolution beyond SAF images. The method was validated using both simulation and experimental data. Results show that the full-width-at-half-maximum of point targets on the elevation plane was reduced compared to using SAF only, suggesting resolution improvement. The proposed method demonstrates the potential to improve 3D image quality of existing linear array-based PA imaging systems, thus benefiting disease diagnostics and follow-up evaluations.


Funder Name

National Institutes of Health (DP5OD028162,R01CA134675)

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